Kernel density estimation on Riemannian manifolds B Pelletier Statistics & probability letters 73 (3), 297-304, 2005 | 200 | 2005 |
Atmospheric correction of satellite ocean-color imagery during the PACE era RJ Frouin, BA Franz, A Ibrahim, K Knobelspiesse, Z Ahmad, B Cairns, ... Frontiers in earth science 7, 145, 2019 | 152 | 2019 |
ERRATA: On the Estimation of the Gradient Lines of a Density and the Consistency of the Mean-Shift Algorithm E Arias-Castro, D Mason, B Pelletier Journal of Machine Learning Research 17 (206), 1-4, 2016 | 121 | 2016 |
Retrieving of particulate matter from optical measurements: A semiparametric approach B Pelletier, R Santer, J Vidot Journal of Geophysical Research: Atmospheres 112 (D6), 2007 | 110 | 2007 |
Non-parametric regression estimation on closed Riemannian manifolds B Pelletier Journal of Nonparametric Statistics 18 (1), 57-67, 2006 | 81 | 2006 |
A graph-based estimator of the number of clusters G Biau, B Cadre, B Pelletier ESAIM: Probability and Statistics 11, 272-280, 2007 | 56 | 2007 |
Exact rates in density support estimation G Biau, B Cadre, B Pelletier Journal of Multivariate Analysis 99 (10), 2185-2207, 2008 | 47 | 2008 |
Remember the curse of dimensionality: The case of goodness-of-fit testing in arbitrary dimension E Arias-Castro, B Pelletier, V Saligrama Journal of Nonparametric Statistics 30 (2), 448-471, 2018 | 45 | 2018 |
Bayesian methodology for inverting satellite ocean-color data R Frouin, B Pelletier Remote Sensing of Environment 159, 332-360, 2015 | 39 | 2015 |
Estimation of density level sets with a given probability content B Cadre, B Pelletier, P Pudlo Journal of Nonparametric Statistics 25 (1), 261-272, 2013 | 33 | 2013 |
The normalized graph cut and Cheeger constant: from discrete to continuous E Arias-Castro, B Pelletier, P Pudlo Advances in Applied Probability 44 (4), 907-937, 2012 | 33 | 2012 |
A kernel-based classifier on a Riemannian manifold JM Loubes, B Pelletier Statistics & Decisions 26 (1), 35-51, 2008 | 30 | 2008 |
Asymptotic normality in density support estimation G Biau, B Cadre, D Mason, B Pelletier | 28 | 2009 |
Perturbation bounds for procrustes, classical scaling, and trilateration, with applications to manifold learning E Arias-Castro, A Javanmard, B Pelletier Journal of Machine Learning Research 21 (15), 1-37, 2020 | 26 | 2020 |
Informative barycentres in statistics B Pelletier Annals of the Institute of Statistical Mathematics 57, 767-780, 2005 | 26 | 2005 |
On the Convergence of Maximum Variance Unfolding. E Arias-Castro, B Pelletier Journal of Machine Learning Research 14 (7), 2013 | 25 | 2013 |
Operator norm convergence of spectral clustering on level sets B Pelletier, P Pudlo The Journal of Machine Learning Research 12, 385-416, 2011 | 21 | 2011 |
Maximum entropy solution to ill-posed inverse problems with approximately known operator JM Loubes, B Pelletier Journal of Mathematical Analysis and Applications 344 (1), 260-273, 2008 | 21 | 2008 |
On the estimation of latent distances using graph distances E Arias-Castro, A Channarond, B Pelletier, N Verzelen | 18 | 2021 |
On the consistency of the crossmatch test E Arias-Castro, B Pelletier Journal of Statistical Planning and Inference 171, 184-190, 2016 | 18 | 2016 |